Due to the non-stationarity of EEG signals, online training and adaptation is essential to EEG based brain-computer interface (BCI) systems. Asynchronous BCI offers more natural human-machine interaction, but it is a great challenge to train and adapt an asynchronous BCI online because the user’s control intention and timing are usually unknown. This paper proposes a novel motor imagery based a...

(E)-2-benzylidene-3-(cyclohexylamino)-2,3-dihydro-1H-inden-1-one (BCI) is known as a dual specific phosphatase 1/6 or MAPK inhibitor. However, its precise anti-lung cancer mechanism remains unknown. In this study, the effects of BCI on cell viability were investigated in the non-small cell lung cancer cell lines NCIH1299, A549, and NCI-H460. We confirmed that BCI significantly inhibited the cel...

Recently, spatio-temporal filtering to enhance decoding for Brain-Computer-Interfacing (BCI) has become increasingly popular. In this work, we discuss a novel, fully Bayesian-and thereby probabilistic-framework, called Bayesian Spatio-Spectral Filter Optimization (BSSFO) and apply it to a large data set of 80 non-invasive EEG-based BCI experiments. Across the full frequency range, the BSSFO fra...

The scope of this chapter is limited to applications where a Brain–Computer Interface (BCI) is used as an explicit interaction technique. In other words, we refer here to BCI as input which is voluntarily controlled by the user, rather than as an implicit interaction as in for mental or cognitive state monitoring. Designing applications using BCI as an explicit input technique for users with se...

OBJECTIVE Brain-computer interface (BCI) provide a non-muscular communication channel for patients with impairments of the motor system. A significant number of BCI users is unable to obtain voluntary control of a BCI-system in proper time. This makes methods that can be used to determine the aptitude of a user necessary. METHODS We hypothesized that integrity and connectivity of involved whi...

Severely disabled people, like completely paralyzed persons either with tetraplegia or similar disabilities who cannot use their arms and hands, are often considered as a user group of Brain Computer Interfaces (BCI). In order to achieve high acceptance of the BCI by this user group and their supporters, the BCI system has to be integrated into their support infrastructure. Critical disadvantag...

PURPOSE This study describes the incidence and outcomes of blunt cardiac injury (BCI) in a single trauma intensive care unit (TICU), together with the spectrum of thoracic injuries and cardiac abnormalities seen in BCI. METHODS We performed a retrospective observational study of 169 patients with blunt thoracic trauma admitted from January 2010 to April 2013. BCI was diagnosed using an elevat...

This chapter presents results of our project, which studied whether contactless and airborne ultrasonic tactile display (AUTD) stimuli delivered to a user’s palms could serve as a platform for a brain computer interface (BCI) paradigm. We used six palm positions to evoke combined somatosensory brain responses to implement a novel contactless tactile BCI. This achievement was awarded the top pri...

This paper summarizes two novel ways to extend brain–computer interface (BCI) systems. One way involves hybrid BCIs. A hybrid BCI is a system that combines a BCI with another device to help people send information. Different types of hybrid BCIs are discussed, along with challenges and issues. BCIs are also being extended through intelligent systems. Software that allows high-level control, inc...

This paper discusses simulated on-line unsupervised adaptation of the LDA classifier in order to counteract the harmful effect of non-class related non-stationarities in EEG during BCI sessions. Three types of adaptation procedures were applied to the two large BCI data sets from TU Graz and Berlin BCI project. Our results demonstrate that the unsupervised adaptive classifiers can improve perfo...